Research on measurement method of resource service composition flexibility in service-oriented manufacturing system

Resource service composition (RSC), which has the ability to realise the added-value of resource service, can satisfy the high-quality application demand of customers. However, in the process of RSC, there always are many uncertain factors influencing the dynamics of RSC, which makes the manufacturing task impossible to be completed efficiently and with high quality. In order to deal with the resulting failures of RSC due to these dynamic changes, this article presented the concept of RSC flexibility as well as the idea of RSC optimal-selection based on flexibility, which can enable RSC to adapt to the dynamic changes. First, the related factors affecting the life-cycle of RSC were analysed, and the definition and classification of RSC flexibility were investigated. Then, the quantitative measuring method of RSC flexibility was investigated, which can establish the perfect evaluation system of RSC flexibility and to achieve the RSC optimal-selection based on flexibility. Meantime, several case studies were presented to illustrate the proposed measurement method. Finally, the significance and effectiveness to put forward the RSC flexibility were tested through simulation experiments.

[1]  David D. Yao,et al.  Material and information flows in flexible manufacturing systems , 1985 .

[2]  Vinod Kumar,et al.  Entropic measures of manufacturing flexibility , 1987 .

[3]  Percy H. Brill,et al.  On measures of flexibility in manufacturing systems , 1989 .

[4]  Suresh P. Sethi,et al.  Flexibility in manufacturing: A survey , 1990 .

[5]  William C. Jordan,et al.  Principles on the benefits of manufacturing process flexibility , 1995 .

[6]  George Chryssolouris,et al.  Flexibility and Its Measurement , 1996 .

[7]  A. Gunasekaran,et al.  Agile manufacturing: The drivers, concepts and attributes , 1999 .

[8]  Weiming Shen,et al.  A multi-resolution collaborative architecture for web-centric global manufacturing , 2000, Inf. Sci..

[9]  Yi-Chih Hsieh,et al.  An approach to the measurement of single-machine flexibility , 2001 .

[10]  Qingyu Zhang,et al.  Manufacturing flexibility: Defining and analyzing relationships among competence, capability, and customer satisfaction , 2003 .

[11]  Mangala Gowri Nanda,et al.  Synchronization analysis for decentralizing composite Web services , 2003, SAC '03.

[12]  Kunal Verma,et al.  Constraint driven Web service composition in METEOR-S , 2004, IEEE International Conference onServices Computing, 2004. (SCC 2004). Proceedings. 2004.

[13]  A.Y. Chang.  On the measurement of labor flexibility , 2004, 2004 IEEE International Engineering Management Conference (IEEE Cat. No.04CH37574).

[14]  Anne H. H. Ngu,et al.  QoS-aware middleware for Web services composition , 2004, IEEE Transactions on Software Engineering.

[15]  Mathias Weske,et al.  Automated planning in a service-oriented architecture , 2004, 13th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises.

[16]  Frances M. T. Brazier,et al.  Composing Web Services using an Agent Factory , 2004, AAMAS 2004.

[17]  Modeling Complexity , 2005, Science.

[18]  Nadia Bhuiyan,et al.  Entropy as a measure of operational flexibility , 2005, Eur. J. Oper. Res..

[19]  Seyed M. R. Iravani,et al.  Structural Flexibility: A New Perspective on the Design of Manufacturing and Service Operations , 2005, Manag. Sci..

[20]  Zakaria Maamar,et al.  Toward an agent-based and context-oriented approach for Web services composition , 2005, IEEE Transactions on Knowledge and Data Engineering.

[21]  Mihhail Matskin,et al.  Composition of Semantic Web services using Linear Logic theorem proving , 2006, Inf. Syst..

[22]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[23]  Farhad Mavaddat,et al.  A Graph-Based Framework for Composition of Stateless Web Services , 2006, 2006 European Conference on Web Services (ECOWS'06).

[24]  George Chryssolouris,et al.  DESYMA: assessing flexibility for the lifecycle of manufacturing systems , 2007 .

[25]  Peter Matthews,et al.  Meta-design for agile concurrent product design in the virtual enterprise , 2007 .

[26]  An-Yuan Chang,et al.  On the measurement of routing flexibility: A multiple attribute approach , 2007 .

[27]  George Chryssolouris,et al.  Quantifying the flexibility of a manufacturing system by applying the transfer function , 2007, Int. J. Comput. Integr. Manuf..

[28]  Marco Pistore,et al.  Handbook of Knowledge Representation Edited Automated Planning , 2022 .

[29]  Lifeng Xi,et al.  Service-oriented communication architecture for automated manufacturing system integration , 2008, Int. J. Comput. Integr. Manuf..

[30]  Shankar Ponnekanti,et al.  SWORD: A Developer Toolkit for Web Service Composition , 2008 .

[31]  Fei Tao,et al.  Resource Service Composition and Its Optimal-Selection Based on Particle Swarm Optimization in Manufacturing Grid System , 2008, IEEE Transactions on Industrial Informatics.

[32]  Fei Tao,et al.  Study on manufacturing grid & its resource service optimal-selection system , 2008 .

[33]  George Chryssolouris,et al.  Modelling the complexity of manufacturing systems using nonlinear dynamics approaches , 2009 .

[34]  Fei Tao,et al.  An approach to manufacturing grid resource service scheduling based on trust-QoS , 2009, Int. J. Comput. Integr. Manuf..

[35]  Fei Tao,et al.  Application and modeling of resource service trust-QoS evaluation in manufacturing grid system , 2009 .

[36]  Fei Tao,et al.  Resource service optimal-selection based on intuitionistic fuzzy set and non-functionality QoS in manufacturing grid system , 2010, Knowledge and Information Systems.

[37]  An-Yuan Chang,et al.  An attribute approach to the measurement of machine-group flexibility , 2009, Eur. J. Oper. Res..

[38]  Fei Tao,et al.  Correlation-aware resource service composition and optimal-selection in manufacturing grid , 2010, Eur. J. Oper. Res..

[39]  Fei Tao,et al.  Correlation-aware web services composition and QoS computation model in virtual enterprise , 2010 .

[40]  Xionghui Zhou,et al.  Internet-based intelligent service-oriented system architecture for collaborative product development , 2010, Int. J. Comput. Integr. Manuf..

[41]  George Q. Huang,et al.  Optimal service selection and composition for service-oriented manufacturing network , 2011, Int. J. Comput. Integr. Manuf..

[42]  George Chryssolouris,et al.  A method for comparing flexibility performance for the lifecycle of manufacturing systems under capacity planning constraints , 2011 .

[43]  Andrew Y. C. Nee,et al.  A review of the application of grid technology in manufacturing , 2011 .

[44]  Fei Tao,et al.  Cloud manufacturing: a computing and service-oriented manufacturing model , 2011 .

[45]  Lei Ren,et al.  Cloud manufacturing: a new manufacturing paradigm , 2014, Enterp. Inf. Syst..